Paper Info
Title
Relative compositionality of multi-word expressions: a study of verb-noun (v-n) collocations
Abstract
Recognition of Multi-word Expressions (MWEs) and their relative compositionality are crucial to Natural Language Processing. Various statistical techniques have been proposed to recognize MWEs. In this paper, we integrate all the existing statistical features and investigate a range of classifiers for their suitability for recognizing the non-compositional Verb-Noun (V-N) collocations. In the task of ranking the V-N collocations based on their relative compositionality, we show that the correlation between the ranks computed by the classifier and human ranking is significantly better than the correlation between ranking of individual features and human ranking. We also show that the properties ‘Distributed frequency of object' (as defined in [27] ) and ‘Nearest Mutual Information' (as adapted from [18]) contribute greatly to the recognition of the non-compositional MWEs of the V-N type and to the ranking of the V-N collocations based on their relative compositionality.
Year
DOI
Venue
2005
10.1007/11562214_49
IJCNLP
Keywords
Field
DocType
multi-word expression,multi-word expressions,relative compositionality,non-compositional mwes,existing statistical feature,human ranking,various statistical technique,natural language processing,nearest mutual information,non-compositional verb-noun,v-n type,noun
Principle of compositionality,Verb,Pattern recognition,Ranking,Expression (mathematics),Computer science,Noun,Artificial intelligence,Natural language processing,Mutual information,Classifier (linguistics),Latent semantic analysis
Conference
Volume
ISSN
ISBN
3651
0302-9743
3-540-29172-5
Citations 
PageRank 
References 
2
0.77
15
Authors
2
Name
Order
Citations
PageRank
Sriram Venkatapathy1689.39
Aravind K. Joshi23479791.99